Publications of the year

Doctoral Dissertations and Habilitation Theses

  • 1F. Heinrich.

    Modeling, Prediction and Optimization of Energy Consumption of MPI Applications using SimGrid, Université Grenoble Alpes, May 2019.

  • 2A. Marcastel.

    Optimisation en ligne et apprentissage adaptatif pour les réseaux dans les bandes ISM, Université de Cergy Pontoise, February 2019.
  • 3P. Mertikopoulos.

    Online optimization and learning in games: Theory and applications, Grenoble 1 UGA - Université Grenoble Alpes, December 2019, Habilitation à diriger des recherches.

  • 4U. Ozeer.

    Autonomic Resilience of Distributed IoT Applications in the Fog, UGA - Université Grenoble Alpes ; MSTII, December 2019.

Articles in International Peer-Reviewed Journals

  • 5P. Alliez, R. Di Cosmo, B. Guedj, A. Girault, M.-S. Hacid, A. Legrand, N. P. Rougier.

    Attributing and Referencing (Research) Software: Best Practices and Outlook from Inria, in: Computing in Science & Engineering, 2019, pp. 1-14, https://arxiv.org/abs/1905.11123. [ DOI : 10.1109/MCSE.2019.2949413 ]

  • 6J. Anselmi.

    Combining Size-Based Load Balancing with Round-Robin for Scalable Low Latency, in: IEEE Transactions on Parallel and Distributed Systems, 2019, pp. 1-3, forthcoming. [ DOI : 10.1109/TPDS.2019.2950621 ]

  • 7J. Anselmi, J. Doncel.

    Asymptotically Optimal Size-Interval Task Assignments, in: IEEE Transactions on Parallel and Distributed Systems, 2019, vol. 30, no 11, pp. 2422-2433. [ DOI : 10.1109/TPDS.2019.2920121 ]

  • 8J. Anselmi, F. Dufour.

    Power-of-d-Choices with Memory: Fluid Limit and Optimality, in: Mathematics of Operations Research, 2019, pp. 1-31, forthcoming.

  • 9I. M. Bomze, P. Mertikopoulos, W. Schachinger, M. Staudigl.

    Hessian barrier algorithms for linearly constrained optimization problems, in: SIAM Journal on Optimization, 2019, vol. 29, pp. 2100 - 2127. [ DOI : 10.1137/18M1215682 ]

  • 10J. Doncel, N. Gast, B. Gaujal.

    Discrete Mean Field Games: Existence of Equilibria and Convergence, in: Journal of Dynamics and Games, 2019, vol. 6, no 3, pp. 1-19, https://arxiv.org/abs/1909.01209. [ DOI : 10.3934/jdg.2019016 ]

  • 11A. Marcastel, E.-V. Belmega, P. Mertikopoulos, I. Fijalkow.

    Online Power Optimization in Feedback-Limited, Dynamic and Unpredictable IoT Networks, in: IEEE Transactions on Signal Processing, 2019, vol. 67, no 11, pp. 2987 - 3000, forthcoming. [ DOI : 10.1109/TSP.2019.2910479 ]

  • 12P. Mertikopoulos, Z. Zhou.

    Learning in games with continuous action spaces and unknown payoff functions, in: Mathematical Programming, Series A, 2019, vol. 173, no 1-2, pp. 465-507, https://arxiv.org/abs/1608.07310. [ DOI : 10.1007/s10107-018-1254-8 ]

  • 13X. Wu, P. Loiseau, E. Hyytiä.

    Towards Designing Cost-Optimal Policies to Utilize IaaS Clouds with Online Learning, in: IEEE Transactions on Parallel and Distributed Systems, 2019, vol. 14, forthcoming. [ DOI : 10.1109/TPDS.2019.2935199 ]


International Conferences with Proceedings

  • 14A. Andreou, M. Silva, F. Benevenuto, O. Goga, P. Loiseau, A. Mislove.

    Measuring the Facebook Advertising Ecosystem, in: NDSS 2019 - Proceedings of the Network and Distributed System Security Symposium, San Diego, United States, February 2019, pp. 1-15. [ DOI : 10.14722/ndss.2019.23280 ]

  • 15K. Antonakopoulos, E.-V. Belmega, P. Mertikopoulos.

    An adaptive mirror-prox algorithm for variational inequalities with singular operators, in: NeurIPS 2019, Vancouver, Canada, 2019.

  • 16P. Bruel, S. Quinito Masnada, B. Videau, A. Legrand, J.-M. Vincent, A. Goldman.

    Autotuning under Tight Budget Constraints: A Transparent Design of Experiments Approach, in: CCGrid 2019 - International Symposium in Cluster, Cloud, and Grid Computing, Larcana, Cyprus, May 2019, pp. 1-10. [ DOI : 10.1109/CCGRID.2019.00026 ]

  • 17A. Chakraborty, G. K. Patro, N. Ganguly, K. P. Gummadi, P. Loiseau.

    Equality of Voice: Towards Fair Representation in Crowdsourced Top-K Recommendations, in: FAT* 2019 - ACM Conference on Fairness, Accountability, and Transparency, Atlanta, United States, Proceedings of the ACM Conference on Fairness, Accountability, and Transparency (FAT*), ACM, January 2019, pp. 129-138. [ DOI : 10.1145/3287560.3287570 ]

  • 18T. Cornebize, A. Legrand, F. C. Heinrich.

    Fast and Faithful Performance Prediction of MPI Applications: the HPL Case Study, in: 2019 IEEE International Conference on Cluster Computing (CLUSTER), Albuquerque, United States, 2019 IEEE International Conference on Cluster Computing (CLUSTER), September 2019. [ DOI : 10.1109/CLUSTER.2019.8891011 ]

  • 19B. Donassolo, I. Fajjari, A. Legrand, P. Mertikopoulos.

    Fog Based Framework for IoT Service Provisioning, in: CCNC 2019 - IEEE Consumer Communications & Networking Conference, Las Vegas, United States, IEEE, January 2019, pp. 1-6. [ DOI : 10.1109/CCNC.2019.8651835 ]

  • 20J. Doncel, N. Gast, M. Tribastone, M. Tschaikowski, A. Vandin.

    UTOPIC: Under-Approximation Through Optimal Control, in: QEST 2019 - 16th International Conference on Quantitative Evaluation of SysTems, Glasgow, United Kingdom, Springer, September 2019, pp. 277-291. [ DOI : 10.1007/978-3-030-30281-8_16 ]

  • 21V. Emelianov, G. Arvanitakis, N. Gast, K. P. Gummadi, P. Loiseau.

    The Price of Local Fairness in Multistage Selection, in: IJCAI-2019 - Twenty-Eighth International Joint Conference on Artificial Intelligence, Macao, France, International Joint Conferences on Artificial Intelligence Organization, May 2019, pp. 5836-5842, https://arxiv.org/abs/1906.06613. [ DOI : 10.24963/ijcai.2019/809 ]

  • 22B. Gaujal, A. Girault, S. Plassart.

    A Linear Time Algorithm for Computing Off-line Speed Schedules Minimizing Energy Consumption, in: MSR 2019 - 12ème Colloque sur la Modélisation des Systèmes Réactifs, Angers, France, November 2019, pp. 1-14.

  • 23Y.-G. Hsieh, F. Iutzeler, J. Malick, P. Mertikopoulos.

    On the convergence of single-call stochastic extra-gradient methods, in: NeurIPS 2019, Vancouver, Canada, 2019, https://arxiv.org/abs/1908.08465 - 27 pages, 3 figures.

  • 24B. Jonglez, S. Birbalta, M. Heusse.

    Persistent DNS connections for improved performance, in: NETWORKING 2019 - IFIP Networking 2019, Warsaw, Poland, May 2019, pp. 1-2.

  • 25N. Liakopoulos, A. S. Destounis, G. Paschos, T. Spyropoulos, P. Mertikopoulos.

    Cautious regret minimization: Online optimization with long-term budget constraints, in: ICML 2019 - 36th International Conference on Machine Learning, Long Beach, United States, June 2019, pp. 1-9.

  • 26P. Mertikopoulos, B. Lecouat, H. Zenati, C.-S. Foo, V. Chandrasekhar, G. Piliouras.

    Optimistic Mirror Descent in Saddle-Point Problems: Going the Extra (Gradient) Mile, in: ICLR 2019 - 7th International Conference on Learning Representations, New Orleans, United States, May 2019, pp. 1-23.

  • 27M. Minaei, M. Mondal, P. Loiseau, K. P. Gummadi, A. Kate.

    Forgetting the Forgotten with Lethe: Conceal Content Deletion from Persistent Observers, in: PETS 2019 - 19th Privacy Enhancing Technologies Symposium, Stockholm, Sweden, July 2019, pp. 1-21.

  • 28U. Ozeer, L. Letondeur, F.-G. Ottogalli, G. Salaün, J.-M. Vincent.

    Designing and Implementing Resilient IoT Applications in the Fog: A Smart Home Use Case, in: ICIN 2019 - 22nd Conference on Innovation in Clouds, Internet and Networks, Paris, France, IEEE, February 2019, pp. 230-232. [ DOI : 10.1109/ICIN.2019.8685909 ]

  • 29D. Quan Vu, P. Loiseau, A. Silva, L. Tran-Thanh.

    Path Planning Problems with Side Observations—When Colonels Play Hide-and-Seek, in: AAAI 2020 - Thirty-Fourth AAAI Conference on Artificial Intelligence, New-York, United States, February 2020, pp. 1-15.

  • 30M. Staudigl, P. Mertikopoulos.

    Convergent Noisy forward-backward-forward algorithms in non-monotone variational inequalities, in: LSS 2019 - 15th IFAC Symposium on Large Scale Complex Systems: Theory and Applications, Delft, Pays-Bas, May 2019, pp. 120-125. [ DOI : 10.1016/j.ifacol.2019.06.021 ]

  • 31L. Vigneri, G. Paschos, P. Mertikopoulos.

    Large-Scale Network Utility Maximization: Countering Exponential Growth with Exponentiated Gradients, in: INFOCOM 2019 - IEEE International Conference on Computer Communications, Paris, France, IEEE, April 2019, pp. 1630-1638. [ DOI : 10.1109/INFOCOM.2019.8737600 ]

  • 32S. Yasodharan, P. Loiseau.

    Nonzero-sum Adversarial Hypothesis Testing Games, in: NeurIPS 2019 - Thirty-third Conference on Neural Information Processing Systems, Vancouver, Canada, 2019, pp. 1-23.


Conferences without Proceedings

  • 33E. Agullo, A. Buttari, A. Guermouche, A. Legrand, I. Masliah, L. Stanisic.

    Simulation of a Sparse Direct Solver on Heterogeneous Systems using Starpu and Simgrid, in: CSE 2019 - SIAM Conference on Computational Science and Engineering, Spokane, United States, SIAM, February 2019.

  • 34J. Assunção, J.-M. Vincent, P. Fernandes.

    Piecewise Aggregation for HMM fitting. A pre-fitting model for seamless integration with time series data, in: SEKE 2019 - 31st International Conference on Software Engineering and Knowledge Engineering, Lisbon, Portugal, July 2019, pp. 729-734. [ DOI : 10.18293/SEKE2019-185 ]

  • 35T.-E. Kennouche, F. Cadoux, N. Gast, B. Vinot.

    ASGriDS: Asynchronous Smart-Grids Distributed Simulator, in: APPEEC 2019 - 11th IEEE PES Asia-Pacific Power and Energy Engineering Conference, Macao, Macau SAR China, IEEE, December 2019, pp. 1-5.

  • 36A. Legrand, D. Trystram, S. Zrigui.

    Adapting Batch Scheduling to Workload Characteristics: What can we expect From Online Learning?, in: IPDPS 2019 - 33rd IEEE International Parallel & Distributed Processing Symposium, Rio de Janeiro, Brazil, IEEE, May 2019, pp. 686-695. [ DOI : 10.1109/IPDPS.2019.00077 ]

  • 37A. Marcastel, E.-V. Belmega, P. Mertikopoulos, I. Fijalkow.

    Gradient-free Online Resource Allocation Algorithms for Dynamic Wireless Networks, in: SPAWC 2019 - 20th IEEE International Workshop on Signal Processing Advances in Wireless Communications, Cannes, France, IEEE, July 2019, pp. 1-4. [ DOI : 10.1109/SPAWC.2019.8815409 ]

  • 38D. Quan Vu, P. Loiseau, A. Silva.

    Combinatorial Bandits for Sequential Learning in Colonel Blotto Games, in: CDC 2019 - 58th IEEE Conference on Decision and Control, Nice, France, December 2019, https://arxiv.org/abs/1909.04912.


Scientific Books (or Scientific Book chapters)

  • 39L. Desquilbet, S. Granger, B. Hejblum, A. Legrand, P. Pernot, N. P. Rougier, E. de Castro Guerra, M. Courbin-Coulaud, L. Duvaux, P. Gravier, G. Le Campion, S. Roux, F. Santos.

    Towards reproducible research : Evolve your practices, Unité régionale de formation à l'information scientifique et technique de Bordeaux, May 2019, pp. 1-161.


Internal Reports

  • 40T. Cornebize, A. Legrand.

    DGEMM performance is data-dependent, Université Grenoble Alpes ; Inria ; CNRS, December 2019, no RR-9310, https://arxiv.org/abs/1912.05381.

  • 41B. Gaujal, A. Girault, S. Plassart.

    A Discrete Time Markov Decision Process for Energy Minimization Under Deadline Constraints, Grenoble Alpes ; Inria Grenoble Rhône-Alpes, Université de Grenoble, December 2019, no RR-9309, 46 p.

  • 42B. Gaujal, A. Girault, S. Plassart.

    Exploiting Job Variability to Minimize Energy Consumption under Real-Time Constraints, Inria Grenoble Rhône-Alpes, Université de Grenoble ; Université Grenoble - Alpes, November 2019, no RR-9300, 23 p.

  • 43B. Gaujal, A. Girault, S. Plassart.

    Feasibility of on-line speed policies in real-time systems, Inria Grenoble Rhône-Alpes, Université de Grenoble ; Univ. Grenoble Alpes, November 2019, no RR-9301, 38 p.



  • 44S. Archipoff, C. Augonnet, O. Aumage, G. Beauchamp, B. Bramas, A. Buttari, A. Cassagne, J. Clet-Ortega, T. Cojean, N. Collin, V. Danjean, A. Denis, L. Eyraud-Dubois, N. Furmento, S. Henry, A. Hugo, M. Juhoor, A. Juven, M. Keryell-Even, Y. Khorsi, T. Lambert, E. Leria, B. Lizé, M. Makni, S. Nakov, R. Namyst, L. Nesi Lucas, J. Pablo, D. Pasqualinotto, S. Pitoiset, N. Quôc-Dinh, C. Roelandt, C. Sakka, C. Salingue, L. Mello Schnorr, M. Sergent, A. Simonet, L. Stanisic, S. Bérangère, F. Tessier, S. Thibault, V. Brice, L. Villeveygoux, P.-A. Wacrenier.

    StarPU, January 2020, Version : 1.3.3,

    [ SWH-ID : swh:1:dir:b6e19d99449a78805e7a55a341fbaba2bc431973 ]
    , Software.


Other Publications

References in notes
  • 51R. M. Badia, J. Labarta, J. Giménez, F. Escalé.

    Dimemas: Predicting MPI Applications Behaviour in Grid Environments, in: Proc. of the Workshop on Grid Applications and Programming Tools, June 2003.
  • 52C. Baier, B. Haverkort, H. Hermanns, J.-P. Katoen.

    Model-checking algorithms for continuous-time Markov chains, in: Software Engineering, IEEE Transactions on, 2003, vol. 29, no 6.

  • 53A. Basu, S. Fleming, J. Stanier, S. Naicken, I. Wakeman, V. K. Gurbani.

    The State of Peer-to-peer Network Simulators, in: ACM Computing Survey., August 2013, vol. 45, no 4.
  • 54D. Becker, F. Wolf, W. Frings, M. Geimer, B. Wylie, B. Mohr.

    Automatic Trace-Based Performance Analysis of Metacomputing Applications, in: Parallel and Distributed Processing Symposium, 2007. IPDPS 2007. IEEE International, March 2007.

  • 55P. Bedaride, A. Degomme, S. Genaud, A. Legrand, G. Markomanolis, M. Quinson, M. L. Stillwell, F. Suter, B. Videau.

    Toward Better Simulation of MPI Applications on Ethernet/TCP Networks, in: PMBS13 - 4th International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems, Denver, United States, November 2013.

  • 56G. Bianchi.

    Performance analysis of the IEEE 802.11 distributed coordination function, in: Selected Areas in Communications, IEEE Journal on, 2000, vol. 18, no 3.
  • 57L. Bobelin, A. Legrand, M. A. G. David, P. Navarro, M. Quinson, F. Suter, C. Thiery.

    Scalable Multi-Purpose Network Representation for Large Scale Distributed System Simulation, in: CCGrid 2012 – The 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, Ottawa, Canada, May 2012, 19 p.

  • 58L. Bortolussi, J. Hillston.

    Model checking single agent behaviours by fluid approximation, in: Information and Computation, 2015, vol. 242.

  • 59L. Bortolussi, R. Lanciani.

    Model Checking Markov Population Models by Central Limit Approximation, in: Quantitative Evaluation of Systems, Lecture Notes in Computer Science, Springer Berlin Heidelberg, 2013, no 8054.
  • 60L. Bortolussi, R. Lanciani.

    Fluid Model Checking of Timed Properties, in: Formal Modeling and Analysis of Timed Systems, Springer International Publishing, 2015.
  • 61H. Brunst, D. Hackenberg, G. Juckeland, H. Rohling.

    Comprehensive Performance Tracking with Vampir 7, in: Tools for High Performance Computing 2009, M. S. Müller, M. M. Resch, A. Schulz, W. E. Nagel (editors), Springer Berlin Heidelberg, 2010.

  • 62A. Busic, B. Gaujal, G. Gorgo, J.-M. Vincent.

    PSI2 : Envelope Perfect Sampling of Non Monotone Systems, in: QEST 2010 - International Conference on Quantitative Evaluation of Systems, Williamsburg, VA, United States, IEEE, September 2010, pp. 83-84.

  • 63A. Busic, B. Gaujal, F. Perronnin.

    Perfect Sampling of Networks with Finite and Infinite Capacity Queues, in: 19th International Conference on Analytical and Stochastic Modelling Techniques and Applications (ASMTA) 2012, Grenoble, France, K. Al-Begain, D. Fiems, J.-M. Vincent (editors), Lecture Notes in Computer Science, Springer, 2012, vol. 7314, pp. 136-149. [ DOI : 10.1007/978-3-642-30782-9_10 ]

  • 64S. Böhm, C. Engelmann.

    xSim: The Extreme-Scale Simulator, in: Proceedings of the International Conference on High Performance Computing and Simulation (HPCS) 2011, Istanbul, Turkey, IEEE Computer Society, Los Alamitos, CA, USA, July 2011.
  • 65H. Casanova, A. Giersch, A. Legrand, M. Quinson, F. Suter.

    Versatile, Scalable, and Accurate Simulation of Distributed Applications and Platforms, in: Journal of Parallel and Distributed Computing, June 2014, vol. 74, no 10, pp. 2899-2917. [ DOI : 10.1016/j.jpdc.2014.06.008 ]

  • 66A. Chaintreau, J.-Y. Le Boudec, N. Ristanovic.

    The Age of Gossip: Spatial Mean Field Regime, in: SIGMETRICS Perform. Eval. Rev., June 2009, vol. 37, no 1.

  • 67K. Coulomb, M. Faverge, J. Jazeix, O. Lagrasse, J. Marcoueille, P. Noisette, A. Redondy, C. Vuchener.

    Visual trace explorer (ViTE), October, 2009.
  • 68J. Doncel, N. Gast, B. Gaujal.

    Mean-Field Games with Explicit Interactions, February 2016.

  • 69S. Durand, B. Gaujal, F. Perronnin, J.-M. Vincent.

    A perfect sampling algorithm of random walks with forbidden arcs, in: QEST 2014 - 11th International Conference on Quantitative Evaluation of Systems, Florence, Italy, Springer, September 2014, vol. 8657, pp. 178-193. [ DOI : 10.1007/978-3-319-10696-0_15 ]

  • 70C. Fricker, N. Gast.

    Incentives and redistribution in homogeneous bike-sharing systems with stations of finite capacity, in: EURO Journal on Transportation and Logistics, June 2014, 31 p. [ DOI : 10.1007/s13676-014-0053-5 ]

  • 71C. Fricker, N. Gast, H. Mohamed.

    Mean field analysis for inhomogeneous bike sharing systems, in: AofA, Montreal, Canada, July 2012.

  • 72D. Fudenberg, D. K. Levine.

    The Theory of Learning in Games, Economic learning and social evolution, MIT Press, Cambridge, MA, 1998, vol. 2.
  • 73R. M. Fujimoto.

    Parallel Discrete Event Simulation, in: Commun. ACM, October 1990, vol. 33, no 10.

  • 74N. Gast, B. Gaujal.

    Markov chains with discontinuous drifts have differential inclusion limits, in: Performance Evaluation, 2012, vol. 69, no 12, pp. 623-642. [ DOI : 10.1016/j.peva.2012.07.003 ]

  • 75N. Gast, B. Gaujal, J.-Y. Le Boudec.

    Mean field for Markov Decision Processes: from Discrete to Continuous Optimization, in: IEEE Transactions on Automatic Control, 2012, vol. 57, no 9, pp. 2266–2280. [ DOI : 10.1109/TAC.2012.2186176 ]

  • 76N. Gast, J.-Y. Le Boudec, D.-C. Tomozei.

    Impact of Demand-Response on the Efficiency and Prices in Real-Time Electricity Markets, in: ACM e-Energy 2014, Cambridge, United Kingdom, June 2014. [ DOI : 10.1145/2602044.2602052 ]

  • 77N. Gast, B. Van Houdt.

    Transient and Steady-state Regime of a Family of List-based Cache Replacement Algorithms, in: ACM SIGMETRICS 2015, Portland, United States, June 2015. [ DOI : 10.1145/2745844.2745850 ]

  • 78J. Gonzalez, J. Gimenez, J. Labarta.

    Automatic detection of parallel applications computation phases, in: Parallel and Distributed Processing Symposium, International, 2009, vol. 0.

  • 79M. Heath, J. Etheridge.

    Visualizing the performance of parallel programs, in: IEEE software, 1991, vol. 8, no 5.
  • 80T. Hoefler, T. Schneider, A. Lumsdaine.

    LogGOPSim - Simulating Large-Scale Applications in the LogGOPS Model, in: Proc. of the ACM Workshop on Large-Scale System and Application Performance, June 2010.
  • 81L. Hu, J.-Y. Le Boudec, M. Vojnović.

    Optimal channel choice for collaborative ad-hoc dissemination, in: INFOCOM, 2010 Proceedings IEEE, IEEE, 2010.
  • 82L. V. Kalé, G. Zheng, C. W. Lee, S. Kumar.

    Scaling applications to massively parallel machines using Projections performance analysis tool, in: Future Generation Comp. Syst., 2006, vol. 22, no 3.
  • 83T. G. Kurtz.

    Approximation of population processes, SIAM, 1981, vol. 36.
  • 84Y.-B. Lin, E. D. Lazowska.

    A Time-division Algorithm for Parallel Simulation, in: ACM Trans. Model. Comput. Simul., January 1991, vol. 1, no 1.

  • 85G. Llort, J. González, H. Servat, J. Giménez, J. Labarta.

    On-line Detection of Large-scale Parallel Application's Structure, in: 24th IEEE International Parallel and Distributed Processing Symposium (IPDPS’2010), 2010.
  • 86L. Mello Schnorr, A. Legrand.

    Visualizing More Performance Data Than What Fits on Your Screen, in: Tools for High Performance Computing 2012, A. Cheptsov, S. Brinkmann, J. Gracia, M. M. Resch, W. E. Nagel (editors), Springer Berlin Heidelberg, 2013, pp. 149-162. [ DOI : 10.1007/978-3-642-37349-7_10 ]

  • 87S. Meyn, P. Barooah, A. Busic, J. Ehren.

    Ancillary service to the grid from deferrable loads: the case for intelligent pool pumps in Florida, in: Decision and Control (CDC), 2013 IEEE 52nd Annual Conference on, IEEE, 2013.
  • 88M. Mitzenmacher.

    The power of two choices in randomized load balancing, in: Parallel and Distributed Systems, IEEE Transactions on, 2001, vol. 12, no 10.
  • 89K. Mohror, K. Karavanic, A. Snavely.

    Scalable Event Trace Visualization, in: Euro-Par 2009 – Parallel Processing Workshops, H.-X. Lin, M. Alexander, M. Forsell, A. Knüpfer, R. Prodan, L. Sousa, A. Streit (editors), Lecture Notes in Computer Science, Springer Berlin / Heidelberg, 2010, vol. 6043.

  • 90W. Nagel, A. Arnold, M. Weber, H. Hoppe, K. Solchenbach.

    VAMPIR: Visualization and Analysis of MPI Resources, in: Supercomputer, 1996, vol. 12, no 1.
  • 91V. Pillet, J. Labarta, T. Cortes, S. Girona.

    PARAVER: A tool to visualise and analyze parallel code, in: Proceedings of Transputer and occam Developments, WOTUG-18, Transputer and Occam Engineering, IOS Press, 1995, vol. 44.
  • 92J. Propp, D. Wilson.

    Coupling from the past: a user's guide, in: DIMACS Series on Discrete Mathematics and Theoretical Computer Science, 1998, vol. 41, Microsurveys in discrete probability.
  • 93M. L. Puterman.

    Markov decision processes: discrete stochastic dynamic programming, John Wiley & Sons, 2014.
  • 94D. Reed, P. Roth, R. Aydt, K. Shields, L. Tavera, R. Noe, B. Schwartz.

    Scalable performance analysis: the Pablo performance analysis environment, in: Scalable Parallel Libraries Conference, 1993., Proceedings of the, 1993.
  • 95W. H. Sandholm.

    Population Games and Evolutionary Dynamics, Economic learning and social evolution, MIT Press, Cambridge, MA, 2010.
  • 96W. H. Sandholm, M. Staudigl.

    A Sample Path Large Deviation Principle for a Class of Population Processes, in: arXiv preprint arXiv:1511.07897, 2015.
  • 97H. Servat, G. Llort, J. Giménez, K. Huck, J. Labarta.

    Folding: detailed analysis with coarse sampling, in: Tools for High Performance Computing 2011, Springer Berlin Heidelberg, 2012.
  • 98H. Servat, G. Llort, J. Gonzalez, J. Gimenez, J. Labarta.

    Identifying code phases using piece-wise linear regressions, in: Parallel and Distributed Processing Symposium, 2014 IEEE 28th International, IEEE, 2014.
  • 99B. Shneiderman.

    The eyes have it: A task by data type taxonomy for information visualizations, in: Visual Languages, 1996. Proceedings., IEEE Symposium on, IEEE, 1996.
  • 100M. Tikir, M. Laurenzano, L. Carrington, A. Snavely.

    PSINS: An Open Source Event Tracer and Execution Simulator for MPI Applications, in: Proc. of the 15th International Euro-Par Conference on Parallel Processing, LNCS, Springer, August 2009, no 5704.
  • 101B. Van Houdt.

    A Mean Field Model for a Class of Garbage Collection Algorithms in Flash-based Solid State Drives, in: Proceedings of the ACM SIGMETRICS, New York, NY, USA, SIGMETRICS '13, ACM, 2013.

  • 102P. Velho, L. Mello Schnorr, H. Casanova, A. Legrand.

    On the Validity of Flow-level TCP Network Models for Grid and Cloud Simulations, in: ACM Transactions on Modeling and Computer Simulation, October 2013, vol. 23, no 4.

  • 103J. J. Wilke, K. Sargsyan, J. P. Kenny, B. Debusschere, H. N. Najm, G. Hendry.

    Validation and Uncertainty Assessment of Extreme-Scale HPC Simulation through Bayesian Inference, in: Euro-Par 2013 Parallel Processing: 19th International Conference, Aachen, Germany, August 26-30, 2013. Proceedings, Springer Berlin Heidelberg, Berlin, Heidelberg, 2013.
  • 104F. Wolf, B. Mohr.

    Automatic performance analysis of hybrid MPI/OpenMP applications, in: Journal of Systems Architecture, 2003, vol. 49, no 10-11.
  • 105T. Yang, P. G. Mehta, S. P. Meyn.

    A mean-field control-oriented approach to particle filtering, in: American Control Conference (ACC), 2011, IEEE, 2011.
  • 106L. Ying.

    On the Rate of Convergence of Mean-Field Models: Stein's Method Meets the Perturbation Theory, in: arXiv preprint arXiv:1510.00761, 2015.
  • 107O. Zaki, E. Lusk, W. Gropp, D. Swider.

    Toward Scalable Performance Visualization with Jumpshot, in: International Journal of High Performance Computing Applications, 1999, vol. 13, no 3.

  • 108G. Zheng, G. Kakulapati, L. Kalé.

    BigSim: A Parallel Simulator for Performance Prediction of Extremely Large Parallel Machines, in: Proc. of the 18th International Parallel and Distributed Processing Symposium (IPDPS), April 2004.
  • 109J. C. de Kergommeaux, B. Stein, P. Bernard.

    Paje, an interactive visualization tool for tuning multi-threaded parallel applications, in: Parallel Computing, 2000, vol. 10, no 26, pp. 1253–1274.